Abstract
Motivation
Elementary flux modes (EFMs) are a key tool for analyzing genome-scale metabolic networks, and several methods have been proposed to compute them. Among them, those based on solving linear programming (LP) problems are known to be very efficient if the main interest lies in computing large enough sets of EFMs.
Results
Here, we propose a new method called EFM-Ta that boosts the efficiency rate by analyzing the information provided by the LP solver. We base our method on a further study of the final tableau of the simplex method. By performing additional elementary steps and avoiding trivial solutions consisting of two cycles, we obtain many more EFMs for each LP problem posed, improving the efficiency rate of previously proposed methods by more than one order of magnitude.
Availability and implementation
Software is freely available at https://github.com/biogacop/Boost_LP_EFM.
Contact
[email protected]
Supplementary information
Supplementary data are available at Bioinformatics online.
Direct calculation of elementary flux modes satisfying several biological constraints in genome-scale metabolic networks